[weberc2]

I write Python in my day job and I _always_ start with types. I find they make even prototype code so much easier to reason about. It's just nice to be able to tell at a glance what a function returns, what args it takes, etc., and I don't have to master Sphinx's cryptic syntax (which I still haven't managed after using it for 5 years). And I experience this benefit even for code that I wrote yesterday without even running the type checker. And it's only going to get better with editor integration.

Without types, if I have the code `a = foo(x=1)` then I have to hunt down the source file for `foo()`, which likely just returns `bar(x)`, so I have to hunt down the source file for `bar()` to figure out what the hell its return type is, and so on and so forth. With types, I just look at the type signature for `foo()` and I'm good to go (and again, editor integration means that I don't even need to look up `foo()` at all!).

YMMV.

[sametmax]

> I write Python in my day job and I _always_ start with types.

It depends of the project. If you write a lot of flask/django code, writing the types is not that worth it except for a few functions/methods.

> Without types, if I have the code `a = foo(x=1)` then I have to hunt down the source file for `foo()`

No, you just hover the function and get the help() out of it in most framework and libs. Again, if your code is mainly using a well define, documented and popular framework/lib/api, that's not a big deal. And it certainly doesn't require YOU to add types.

Or if you write a program that is contained in 1 to 5 files top. Not use for types.

Or if you are writing your program in jupyter.

And you most likely copy a snipet from the doc anyway. After all, if you see that the function you want to use return a AbstractTranscientVectorServiceFactory object, you can't do much with the information without the doc anyway.

But let's be real, most functions in Python are named pretty explicitly, and return things that you expect like "iterable of numbers" or "file like object yielding utf8".

Types are particularly useful in the cases if you are in a big project with a lot of custom code or in a domain either very complex or that you don't master very well. They are a good for of safety net and documentation at the same time.

But they come at a cost and it's a good thing to be able to choose.

[netheril96]

> No, you just hover the function and get the help() out of it in most framework and libs. Again, if your code is mainly using a well define, documented and popular framework/lib/api, that's not a big deal. And it certainly doesn't require YOU to add types.

If the help or comments tell you the types of arguments and return values, that is just static typing in the form of comments. Even more verbose than language level type annotations, yet much harder to parse for editors/IDEs/linters.

[weberc2]

> No, you just hover the function and get the help() out of it in most framework and libs.

There are no editors that can reliably deliver type information. The ones that come closest (PyCharm and YouCompleteMe) are otherwise very poor editors and resource hogs (the former) or nearly impossible to set up correctly (the latter). And neither is of any use when I'm reviewing someone's code on Github or debugging over ssh.

> Or if you write a program that is contained in 1 to 5 files top. Not use for types.

Types are definitely _useful_ for small programs, but you're right that they're not _necessary_ to the degree that they are for larger programs.

> And you most likely copy a snipet from the doc anyway.

This... is not the kind of programming I do. Although it may explain a lot about our difference of opinion on the topic.

> But let's be real, most functions in Python are named pretty explicitly, and return things that you expect like "iterable of numbers" or "file like object yielding utf8".

Ah yes, the get_values_as_iterable_of_numbers() function. :) Let's be real, virtually _no_ functions are named this way, and even if they were, the typing syntax is surely a better way of facilitating this information. More importantly, it still doesn't tell us anything about the types or number of the arguments. Lots of popular Python libraries (Pandas, Matplotlib) take ridiculous combinations of arguments (two strings and an int sometimes, but other times its an int and a float and a file handle, and if it's called on a Tuesday in April then you can omit all int args). If they had to appease a type checker, these libraries would certainly be much more usable.

> But they come at a cost and it's a good thing to be able to choose.

There are tradeoffs in many areas of programming, but typing is a clear win. Specifically, what is the cost you mention? The type checker won't let your type documentation grow stale? Or perhaps it makes it hard to write clumsy signatures like those in Pandas and Matplotlib?